teg-get-best-n 0.0.1

Estimate the optimal number of components or clusters.

Module of functions for estimating the optimal number of components or clusters.

PCA

Selects the number of components based on comparing eigenvectors between split-halves of the data. I.e., this doesn't use the shape of the eigenvalue curve, but makes a split between components with high versus low split-half similarity.

Usage:

O = teg_get_best_n.get_n_components(X)

This returns a dictionary with the estimated number of components in O['nComponents'], as well as the eigenvalues (O['eigenvalues']) and eigenvectors (O['eigenvectors']).

The file example.py contains tests with simulated data to check how well the true number of latent variables is recovered.